Identification and validation of an 8-gene expression signature for predicting high-Fuhrman grade renal cell carcinoma.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 526-526
Author(s):  
Fangning Wan ◽  
Yao Zhu ◽  
Chengtao Han ◽  
Qinghua Xu ◽  
Bo Dai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Renal Mass ◽  
Gene Expression Signature ◽  
High Grade ◽  
Fuhrman Grade ◽  
Expression Signature ◽  
Biopsy Specimens

526 Background: Clear cell renal cell carcinoma (ccRCC) is a malignancy with heterogeneous outcomes. Currently, renal mass biopsies are commonly employed to extract disease characteristics and aid prognosis. Although the pathological diagnosis of malignant disease is accurate in contemporary reports, the classification of Fuhrman grade using biopsy specimens is still far from promising. Our aim is to generate a signature biomarker to distinguish high grade ccRCC that could be readily applied to clinical biopsy samples. Methods: Using the Cancer Genome Atlas (TCGA) database, a gene expression signature was developed to distinguish high-grade (G3/4) from low-grade (G1/2) disease. The expression profile was further validated for performance and clinical usage in 283 frozen renal cancer samples and 127 ex-vivo renal mass biopsy samples, respectively. The area under curve (AUC) was used to quantify discriminative ability and was compared using the De-long test. Results: Using the development dataset, we identified a 24-gene signature for high-grade disease with an AUC of 0.884. After applied to the replication dataset, an eight-gene profile was defined and achieved an AUC of 0.823. The accuracy of 8-gene panel was maintained in the RMB samples (AUC = 0.821). Conclusions: Using a two-stage replication design, we validated an eight-gene expression signature for predicting high Fuhrman grade of ccRCC. This tool may help to reveal the characteristics of ccRCC biopsy specimens.

scholarly journals Identification and validation of an eight-gene expression signature for predicting high Fuhrman grade renal cell carcinoma

2017 ◽  
Vol 140 (5) ◽  
pp. 1199-1208 ◽  
Author(s):  
Fangning Wan ◽  
Yao Zhu ◽  
Chengtao Han ◽  
Qinghua Xu ◽  
Junlong Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Gene Expression Signature ◽  
Fuhrman Grade ◽  
Expression Signature

205 GENE EXPRESSION SIGNATURE ASSOCIATED WITH METASTASIS IN CLEAR CELL RENAL CELL CARCINOMA

2010 ◽  
Vol 183 (4S) ◽  
Author(s):  
Jimsgene Sanjmyatav ◽  
Thomas Steiner ◽  
Mieczyslaw Gajda ◽  
Heiko Wunderlich ◽  
Kerstin Junker
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Expression Signature ◽  
Cell Renal Cell Carcinoma ◽  
Expression Signature

Histologic Heterogeneity of Extirpated Renal Cell Carcinoma Specimens: Implications for Renal Mass Biopsy

2020 ◽  
Vol 7 (3) ◽  
pp. 20-25
Author(s):  
Lauren Nahouraii ◽  
Jordan Allen ◽  
Suzanne Merrill ◽  
Erik Lehman ◽  
Matthew Kaag ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Renal Mass ◽  
Tumor Stage ◽  
High Grade ◽  
Renal Masses ◽  
Histologic Heterogeneity ◽  
Adequate Sampling ◽  
Renal Mass Biopsy

Pathologic characteristics of extirpated renal cell carcinoma (RCC) specimens <7  cm were reviewed to get better information on technical nuances of renal mass biopsy (RMB). Specimens were stratified according to tumor stage, nuclear grade, size, histology, presence of lymphovas-cular invasion (LVI), necrosis, and sarcomatoid features. When considering pT1 (0–7 cm) tumors pT1b (4–7 cm), RCC masses were more likely to have necrosis (43% vs 16%, P < 0.001), LVI (6% vs 2%, P = 0.024), high-grade nuclear elements (29% vs 17%, P < 0.001), and sarcomatoid features (2% vs 0%, P = 0.006) compared with pT1a (0–4 cm) tumors. Additionally, pT3a tumors were more highly associated with necrosis (P = 0.005), LVI, sarcomatoid features, and high-grade disease (P for all < 0.001) when compared to pT1 masses. For masses <4 cm, pT3a cancers were more likely to demonstrate necrosis (38% vs 16%, P < 0.001), LVI (10% vs 2%, P = 0.037), high-grade nuclear elements (31% vs 17%, P = 0.05), and sarcomatoid features (3% vs 0%, P = 0.065) compared to pT1a tumors. Similarly, for masses 4–7 cm, pathologic T3a tumors were significantly more likely to have sarcomatoid features (16% vs 2%, P < 0.001) and LVI (28% vs 6%, P < 0.001) compared to pT1b tumors. In summary, pT3a tumors and those RCC masses >4 cm exhibit considerable histologic heterogeneity and may harbor elements that are not easily appreciated with limited renal sampling. Therefore, if RMB is considered for renal masses greater than 4 cm or those that abut sinus fat, a multi-quadrant biopsy approach is necessary to ensure adequate sampling and characterization of the mass.

Translocation renal cell carcinomas: An evolving entity.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 472-472
Author(s):  
Richard Martin Bambury ◽  
Claire Brady ◽  
Aoife McCarthy ◽  
Stewart Fleming ◽  
Nicholas J. Mayer ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Transcription Factor ◽  
Cell Carcinoma ◽  
Metastatic Disease ◽  
Renal Cell ◽  
Renal Mass ◽  
Renal Cell Carcinomas ◽  
Fuhrman Grade ◽  
Post Surgery ◽  
Disease Free

472 Background: Translocation renal cell carcinomas (RCCs) are a novel, rare and distinct clinicopathological entity. The term refers to RCCs with overexpression of transcription factor E3 (TFE3) due to translocation involving the Xp11 locus or less commonly with overexpression of transcription factor EB (TFEB) due to a t(6:11) translocation. In children it is estimated that these tumours account for 40% of RCCs but in adults this proportion is estimated to be 1-4%. As these neoplasms are only recently recognised, outcome data are premature. We report 2 cases of translocation RCC in an Irish regional cancer centre and describe clinicopathological characteristics and early outcome. Methods: In our recent practice, 2 renal cell carcinomas were suspected to be translocation tumours based on morphology and immunohistochemical features (RCC+/CK7-/EMA-). Using immunohistochemistry we tested for expression of TFE3 and TFEB. Results: Both tumours were translocation RCCs. The first case was a 74 year old lady who presented with right upper quadrant pain and had a 9cm right renal mass with no metastatic disease on CT imaging. Radical nephrectomy was performed and histology revealed a pT3aN2, Fuhrman grade 4 renal cell carcinoma with papillary architecture and eosinophillic hyaline nodules within many of the papillae. Staining for TFE3 showed focal nuclear positivity consistent with an Xp11 translocation RCC. She remains disease free 6 months post surgery. The second case was a 46 year old man with an incidental finding of a right renal mass on ultrasound abdomen performed after a new diagnosis of haemochromatosis. Staging CT imaging revealed no metastatic disease and he underwent laparoscopic nephrectomy. Histology revealed a pT1aNx, Fuhrman grade 3 renal cell carcinoma with predominantly alveolar architecture and focal papillary and microcystic areas. Staining for TFEB was positive consistent with a t6:11 translocation RCC. He remains disease free 5 months post surgery. Conclusions: We report 2 new cases of this rare subset of RCC. The therapeutic implications for patients with these mutations are as yet unclear. We plan to update with ongoing follow-up and identification of new cases to determine the clinical behaviour of these rare cancers in the Irish setting. 

scholarly journals Differentiation of low and high grade renal cell carcinoma on routine MRI with an externally validated automatic machine learning algorithm

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Subhanik Purkayastha ◽  
Yijun Zhao ◽  
Jing Wu ◽  
Rong Hu ◽  
Aidan McGirr ◽  
...  
Keyword(s):  
Machine Learning ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clinical Decision Making ◽  
External Validation ◽  
Automatic Machine ◽  
Low Grade ◽  
High Grade ◽  
Fuhrman Grade

Abstract Pre-treatment determination of renal cell carcinoma aggressiveness may help guide clinical decision-making. We aimed to differentiate low-grade (Fuhrman I–II) from high-grade (Fuhrman III–IV) renal cell carcinoma using radiomics features extracted from routine MRI. 482 pathologically confirmed renal cell carcinoma lesions from 2008 to 2019 in a multicenter cohort were retrospectively identified. 439 lesions with information on Fuhrman grade from 4 institutions were divided into training and test sets with an 8:2 split for model development and internal validation. Another 43 lesions from a separate institution were set aside for independent external validation. The performance of TPOT (Tree-Based Pipeline Optimization Tool), an automatic machine learning pipeline optimizer, was compared to hand-optimized machine learning pipeline. The best-performing hand-optimized pipeline was a Bayesian classifier with Fischer Score feature selection, achieving an external validation ROC AUC of 0.59 (95% CI 0.49–0.68), accuracy of 0.77 (95% CI 0.68–0.84), sensitivity of 0.38 (95% CI 0.29–0.48), and specificity of 0.86 (95% CI 0.78–0.92). The best-performing TPOT pipeline achieved an external validation ROC AUC of 0.60 (95% CI 0.50–0.69), accuracy of 0.81 (95% CI 0.72–0.88), sensitivity of 0.12 (95% CI 0.14–0.30), and specificity of 0.97 (95% CI 0.87–0.97). Automated machine learning pipelines can perform equivalent to or better than hand-optimized pipeline on an external validation test non-invasively predicting Fuhrman grade of renal cell carcinoma using conventional MRI.

Toward a molecular genetic classification of clear cell renal cell carcinoma.

2013 ◽  
Vol 31 (6_suppl) ◽  
pp. 341-341
Author(s):  
James Brugarolas ◽  
Payal Kapur ◽  
Samuel Pena-Llopis ◽  
Alana Christie ◽  
Xian-Jin Xie
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
The Cancer Genome Atlas ◽  
Genetic Classification ◽  
Cell Renal Cell Carcinoma ◽  
Fuhrman Grade ◽  
Pathologic Features

341 Background: Clear cell renal cell carcinoma (ccRCC) displays a variety of clinical behaviors. However, the molecular underpinnings are unknown. We discovered that BAP1 is mutated in approximately 15% of ccRCC and that BAP1 and PBRM1mutations are largely mutually exclusive. Herein, we investigate the clinicopathological significance of these molecular subtypes. Methods: Tumors from 145 patients with primary ccRCC were sequenced for PBRM1 and BAP1. Tumors were classified into BAP1-mutated and those exclusively mutated for PBRM1. Tumors were evaluated for pathologic features, gene expression and associated outcomes. A second independent cohort (n=327) from The Cancer Genome Atlas (TCGA) was used for validation. Results: When compared to PBRM1-mutant tumors, BAP1-mutant tumors were associated with aggressive pathological features including high Fuhrman grade and tumor necrosis. BAP1-mutant and PBRM1-mutant tumors exhibited distinct gene expression signatures. The median overall survival (OS) was shorter for patients with BAP1-mutant tumors (4.6 years; 95% CI, 2.1-7.2), than for patients with PBRM1-mutant tumors (10.6 years; 95% CI, 9.8-11.5), corresponding to a hazard ratio (HR) of 2.7 (95% CI, 0.99-7.6, p = 0.044). A similar HR was observed in the independent dataset from the TCGA (2.8; 95% CI, 1.4-5.9; p = 0.004). The BAP1-mutant group could be further subdivided into tumors with mutations exclusively in BAP1 and those with mutations in both BAP1 and PBRM1. Double mutant tumors constituted a minority (n = 4; in TCGA), and were associated with the shortest OS (HR, 10; 95% CI, 3.2-33.6). Conclusions: Our findings reveal novel biological subgroups of ccRCC with distinct clinical outcomes, a high-risk BAP1-mutant group and a favorable PBRM1-mutant group. These data establish the basis for a molecular subclassification of ccRCC that could influence treatment decisions in the future.

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